Best Auto Scaling Software for Google Cloud Platform
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Compare the Top Auto Scaling Software that integrates with Google Cloud Platform as of October 2025
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This a list of Auto Scaling software that integrates with Google Cloud Platform. Use the filters on the left to add additional filters for products that have integrations with Google Cloud Platform. View the products that work with Google Cloud Platform in the table below.
What is Auto Scaling Software for Google Cloud Platform?
Auto scaling software helps to optimize the performance of cloud applications. It works by automatically increasing or decreasing the number of underlying resources such as virtual machines, server capacity and storage upon detecting changes in workloads. It allows applications to dynamically scale up or down depending on traffic patterns while keeping costs minimized. Auto scaling is particularly useful when there are predictable changes in application demand over time and for applications with negative elasticity, where additional load can cause a decrease in performance. It has become an essential tool for many organizations utilizing cloud service platforms due to its ability to manage application availability, scalability and performance. Compare and read user reviews of the best Auto Scaling software for Google Cloud Platform currently available using the table below. This list is updated regularly.
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1
Google Compute Engine
Google
Google Compute Engine's auto scaling feature automatically adjusts the number of virtual machine instances in response to fluctuations in traffic or workload demands. This ensures that applications maintain optimal performance without manual intervention and helps to reduce unnecessary costs by scaling down when demand is low. Users can configure scaling policies based on specific criteria, such as CPU utilization or request rate, to further customize how resources are allocated. New customers receive $300 in free credits, enabling them to test and fine-tune auto scaling for their unique workloads.Starting Price: Free ($300 in free credits) -
2
RunPod
RunPod
RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.Starting Price: $0.40 per hour -
3
VMware Avi Load Balancer
Broadcom
Simplify application delivery with software-defined load balancers, web application firewall, and container ingress services for any application in any data center and cloud. Simplify administration with centralized policies and operational consistency across on-premises data centers, and hybrid and public clouds, including VMware Cloud (VMC on AWS, OCVS, AVS, GCVE), AWS, Azure, Google, and Oracle Cloud. Free infrastructure teams from manual tasks and enable DevOps teams with self-service. Application delivery automation toolkits include Python SDK, RESTful APIs, Ansible and Terraform integrations. Gain unprecedented insights, including network, end users and security, with real-time application performance monitoring, closed-loop analytics and deep machine learning. -
4
UbiOps
UbiOps
UbiOps is an AI infrastructure platform that helps teams to quickly run their AI & ML workloads as reliable and secure microservices, without upending their existing workflows. Integrate UbiOps seamlessly into your data science workbench within minutes, and avoid the time-consuming burden of setting up and managing expensive cloud infrastructure. Whether you are a start-up looking to launch an AI product, or a data science team at a large organization. UbiOps will be there for you as a reliable backbone for any AI or ML service. Scale your AI workloads dynamically with usage without paying for idle time. Accelerate model training and inference with instant on-demand access to powerful GPUs enhanced with serverless, multi-cloud workload distribution. -
5
Lucidity
Lucidity
Lucidity is a multi-cloud storage management platform that dynamically resizes block storage across AWS, Azure, and Google Cloud without downtime, enabling enterprises to save up to 70% on storage costs. Lucidity automates the expansion and contraction of storage volumes based on real-time data demands, ensuring optimal disk utilization between 75-80%. This autonomous, application-agnostic solution integrates seamlessly with existing applications and environments, requiring no code changes or manual provisioning efforts. Lucidity's AutoScaler is available on the AWS Marketplace, offering enterprises an automated solution to expand and shrink live EBS volumes based on workload without downtime. By streamlining operations, Lucidity enables IT and DevOps teams to reclaim hundreds of hours, allowing them to focus on higher-impact initiatives that drive innovation and efficiency. -
6
NVIDIA DGX Cloud Serverless Inference is a high-performance, serverless AI inference solution that accelerates AI innovation with auto-scaling, cost-efficient GPU utilization, multi-cloud flexibility, and seamless scalability. With NVIDIA DGX Cloud Serverless Inference, you can scale down to zero instances during periods of inactivity to optimize resource utilization and reduce costs. There's no extra cost for cold-boot start times, and the system is optimized to minimize them. NVIDIA DGX Cloud Serverless Inference is powered by NVIDIA Cloud Functions (NVCF), which offers robust observability features. It allows you to integrate your preferred monitoring tools, such as Splunk, for comprehensive insights into your AI workloads. NVCF offers flexible deployment options for NIM microservices while allowing you to bring your own containers, models, and Helm charts.
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